ESRI Discussion Paper Series No.392

Inequality Dynamics in Japan, 1981-2021
Sagiri Kitao
Tomoaki Yamada
April 2024

Economic and Social Research InstituteCabinet Office
Tokyo, JapanThe views expressed in “ESRI Discussion Papers” are those of the authors and not those of
the Economic and Social Research Institute, the Cabinet Office, or the Government of Japan.
(Contact us: https://form.cao.go.jp/esri/en_opinion-0002.html)

Inequality Dynamics in Japan, 1981-2021∗
Sagiri Kitao

Tomoaki Yamada

GRIPS

Meiji University

Abstract
This paper examines the path of economic inequality in Japan spanning four
decades (1981-2021) using the Family Income and Expenditure Survey. Over thisperiod, inequality in earnings, disposable income, and consumption has widened.
Earnings inequality, measured by the Gini coeﬃcient, exhibited a non-linear increase from 0.24 to 0.29, with a signiﬁcant rise in the 1980s and early 2000s.
Conversely, disposable income showed a modest downward trend since the mid2010s. Despite this, consumption inequality continued to rise moderately, indicating a divergence in the dynamics of disposable income and consumption inequality.
Analysis from a life cycle perspective conﬁrms the diﬀerent shapes of age proﬁlesfor income and consumption inequality. Our ﬁndings also highlight substantial
variations in age-speciﬁc inequality across diﬀerent consumption items.
Keywords: Inequality trends, life cycle inequality, Consumption inequality,
Income inequality
JEL Classiﬁcation: D12, D31, E21, J11∗

We are grateful to Hirokazu Ishise and Yutaka Murayama for helpful comments. The Statistics
Bureau of Japan provided us with the microdata from the Family Income and Expenditure Survey.
This work is supported by JSPS KAKENHI Grant Numbers 18KK0368, 21K01404, 22H00831, and
22H05008. The views expressed in this paper are those of the authors and do not represent those of theinstitution the authors are aﬃliated with.

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

1

Introduction

Since the Great Recession, there has been growing concern about the widening economic
inequality worldwide, as highlighted by movements such as Occupy Wall Street in 2011
and the bestselling book on inequality by Piketty (2014). In addition, the existence oftax havens has heightened the inequality associated with the concentration of wealth. 1
In Japan, interest in economic inequality grew earlier, with books on economic inequality already published in the late 1990s.2 The rising concerns about inequality partly
stem from the collapse of the Japanese employment system, characterized by lifetime
employment and the seniority wage system, as well as the uncertain outlook for theJapanese economy following the burst of the bubble. This study analyzes the transitionof economic inequality in Japan over the last four decades, from 1981 to the present.
Lise et al. (2014) conducted a comprehensive analysis of the dynamics of inequality
in the Japanese economy in 1981-2008 as part of the Review of Economic Dynamics’(RED) special issue project.3 The project aims to make international comparisons ofinequality by aligning the deﬁnitions of variables in each country as much as possible. In
Japan, the analysis was published in 2014, using four sets of microdata: panel data fromthe Japanese Panel Survey of Consumers (JPSC), the Basic Survey on Wage Structure(BSWS), the Family Income and Expenditure Survey (FIES), and the National Surveyof Family Income and Expenditure (NSFIE). All data sets, except for the JPSC, aregovernment statistics, and the analysis was conducted using data from 1981 to 2008,
which was available at the time. Since then, the Japanese economy has undergone various
events, such as the Great Recession, the Great East Japan Earthquake, Abenomics’1
For the recent discussion on global economic inequality, see Saez and Zucman (2019) and Milanovic(2016); ?? (Mil).
2
For example, Tachibanaki (1998) points out the possibility of widening inequality in the late 1990s.
Ohtake and Saito (1998) emphasized that demographic changes signiﬁcantly impacted the rise in economic inequality in the 1970s and 1980s.
3
The project aims to understand the time series and life cycle aspects of economic inequality measured by various aspects such as wages, labor income, consumption, and assets for nine countries (U.S.,
UK, Canada, Germany, Italy, Spain, Sweden, Russia, and Mexico). The results of the special issue aresummarized in Krueger et al. (2010). Japan is added in 2014 (Lise et al. (2014)). Heathcote et al.
(2023) update their data from 1967-2006, conducted by Heathcote et al. (2010), to 1967-2021 for the
U.S. economy. Bryukhanov and Hryshko (2024) also provide an economic inequality analysis of thetime-series direction and life cycle aspects of the Russian economy.

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ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

policy mix of quantitative and qualitative easing and expansionary ﬁscal policy, andthe COVID-19 crisis. All of these are extremely important events for examining thetransition of inequality, and it is also essential to understand the mechanism of inequality
expansion by conﬁrming how these events contributed to the expansion and contractionof inequality. This paper extends the period of their analysis to examine what has
happened with respect to economic inequality in Japan over the last decades with aparticular focus on the most recent decade.
The RED Project also addresses the life cycle aspects of economic inequality, a topic
of increasing relevance given the ongoing demographic changes in Japan. It is widely
known that demographic changes have distinct impacts on economic inequality. For
instance, as Deaton and Paxson (1994), Ohtake and Saito (1998) and Abe and Yamada(2009) show, there is a signiﬁcant diﬀerence in both the level and inequality between
the labor income of young workers and that of older workers. This discrepancy can beinﬂuenced by various factors, including diﬀerences in skills and productivity associatedwith the birth cohort and years of experience, as well as eﬀorts, luck and misfortune.
As Japan’s birthrate declines and its population ages rapidly, understanding how thesedemographic changes aﬀect economic inequality is crucial for predicting their impact on
the Japanese economy.
A unique feature of the RED project is its focus on the analysis of economic inequalities from a macroeconomist’s perspective. Speciﬁcally, the analysis is based onhouseholds’ budget constraints and proceeds on how the idiosyncratic risks faced byhouseholds spill over and aﬀect widening inequality. The budget constraint of households assumed in this paper is a common basis for the so-called Heterogeneous Agent
New Keynesian (HANK) model, which is currently attracting attention as a framework
for analyzing monetary and ﬁscal policy.4 The estimation of idiosyncratic risk itself is
4

In the HANK models, policy analysis focuses on the relationship between economic inequality andmonetary and ﬁscal policy. That is, it discusses how heterogeneity in households and ﬁrms creates
diﬀerences in the eﬀectiveness of economic policies or how ﬁscal and monetary policies aﬀect income
and consumption inequality. The number of analyses using the HANK model has increased rapidly
in recent years; regarding the relationship between heterogeneity and macroeconomic policy, see, forexample, Bilbiie (2008), Inui et al. (2017), Bayer et al. (2018), Kaplan et al. (2018), Bilbiie (2020),
Gornemann et al. (2021), Inaba and Kengo Nutahara (2023).

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ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

not performed in this study because of the inability to distinguish between wages andhours worked due to the limitations of the data set.5 Instead we focus on the time-series
and life cycle dimensions of inequalities in this paper.
Our main research ﬁndings regarding the trends of labor and income inequality are
as follows. First, labor income inequality increased in the 1980s and early 2000s andhas remained high during the following two decades. It is important to note that weare not currently in a phase of rising inequality. Rather, disposable income inequality
has slightly decreased during the Abenomics policy period. Both labor income anddisposable income inequality have increased sharply during the COVID-19 crisis period.
Second, although income and consumption inequality trended in an almost parallel
fashion before 2010, they started to diverge since the beginning of the 2010s. Whilethe inequality in disposable income has declined slightly, consumption inequality has
increased moderately in the 2010s. This discrepancy could be attributed to the permanent income hypothesis, in which households’ consumption decisions depend not only on
current income but also on future income. They may perceive the narrowing of income
inequality as a temporary phenomenon, which is not reﬂected in consumption inequality.
This paper is organized as follows. Section 2 describes details of our data, theFamily Income and Expenditure Survey. In Section 3, we documents the developmentof inequalities in earnings, income, and consumption across Japanese households from1981 to 2021. Section 4 illustrates the life cycle aspects of inequality. In particular, we
focus on the life cycle proﬁles of disaggregated expenditure items. Section 5 concludes.

2

Data

We use the Family Income and Expenditure Survey, which is compiled by the Statistics
Bureau, Ministry of Internal Aﬀairs and Communications.

5

Following the approach by Blundell et al. (2008), Okubo (2015) estimate the size of permanent andtransitory income shocks using microdata of Japanese economy. For recent progress in the estimationof income, see, for example, Arellano et al. (2017).

4

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

2.1

Family Income and Expenditure Survey (FIES)

The FIES is a monthly survey of households that collects information on earnings,
income and expenditures of each household as well as various characteristics of household
members such as their ages, gender, occupation, industry of employment, marital status,
and region of residence.6 In this study, we use 41 years of the survey data from January
1981 to December 2021. The FIES consists of two data sets: (i) households that consist of
two or more members, such as couples and extended families, and (ii) single households.
The FIES started collecting data for single households in January 2002, and the data for
two or more household members are available for the entire sample period. Therefore,
we focus on households with two or more household members for consistency.
The FIES is a rotating panel data that follows the same household for a maximumof six consecutive months, after which another household replaces the household; thesampled households overlap, and one-sixth of the total samples are generally replacedby new households each month. However, since there is no ID to identify the same
household in our data set, the households are connected to form a panel based onhousehold characteristics and prefecture information, following the approach by Stephensand Unayama (2011). Households participate in the survey for a maximum of six months,
but some households drop out during the survey period, resulting in unbalanced panel
data. The sample size for each month is approximately 8,000 households. Since thedata is collected monthly, the FIES is suitable for capturing high-frequency dynamics ofinequality, such as business cycles, in comparison to the Panel Study of Income Dynamics(PSID) and Consumer Expenditure Survey (CEX) in the U.S.
2.1.1

Target Variables

Our analysis focuses on the dynamics of inequality in earnings, income, and consumption.
Regarding the deﬁnition of these three variables, we follow the approach of Heathcote
et al. (2010) and Lise et al. (2014) for international comparisons and consistency. The
6

The FIES is one of the government’s “fundamental statistical surveys.” It is used to calculate theConsumer Price Index in Japan and is also used to calculate private consumption expenditures in theGDP.

5

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

basic idea, as advocated by Heathcote et al. (2010), is to construct variables step-by-stepfrom the following budget constraint of a household:c + a′ = yL + (1 + r)a + b + T,y = yL + ra + b,
yD = yL + ra + b + T,
where c denotes consumption, a is asset holdings, yL is household earnings, r is thereal interest rate, b is private transfers, and T is net public transfers including tax payments and premiums for public pension, health insurance, and long-term care insurance
programs.
We mainly focus on the dynamics of inequality in earnings yL , pre-government income
y, disposable income yD , and consumption c.
2.1.2

Earnings, Asset Income and Disposable Income

In the FIES, each household reports two types of information on income: last year’s
annual income and monthly incomes. Annual income is reported only once for eachhousehold.7 The annual income is the combined total income of all household members
and cannot be separated for each earner. Given these limitations with the annual income
variable, we primarily use monthly earnings of all household members to compute earnings of the household. We also use income information for detailed information abouthousehold ﬁnances such as asset income, taxes, and transfers.
The variables created from the monthly data are as follows: 8 :• Household earning yL : Household earning is the sum of monthly earnings ofhousehold head, his/her spouse and other household members. Monthly earnings
includes regular salary, temporary salary, bonuses and piecework salary.
7

The previous year’s annual income depends on the timing of the survey; for example, a householdthat participated in the survey for the six months from March to August would have reported income
for each month and last year’s annual income for 12 months from last March to this February.
8
For details, see Sudo et al. (2012), and Lise et al. (2014)

6

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"• Pre-government income y: To construct the pre-government income, we add
private transfers b and asset income ra to the household earning yL . The private transfers consist of remittances and gifts. Asset income includes house rents,
property income, and income from self-employment.
• Disposable income yD : To construct the disposable income, we add social security beneﬁts to and subtract taxes and premium for social insurance programsfrom pre-government income y. The social insurance premium consists of premiumfor public pension, health insurance, and long-term care insurance programs. The
taxes consists of income taxes, residence taxes and other taxes.
All variables related to income are deﬂated using the CPI. We equivalize all variables
using the OECD equivalent scale following the convention in the RED Project.
2.1.3

Consumption/Expenditure

FIES sample households are required to keep a monthly household account book andsubmit it at the end of the survey period. Therefore, the information on expenditures
is considered more accurate than that in so-called recall data such as the PSID. The
deﬁnitions of the expenditure variables we focused on this analysis are as follows.
• Non-durable expenditure cN D : As for the non-durable expenditure, we follow
the deﬁnition by the Ministry of Internal Aﬀairs and Communications. Thus, cN D
consists of general food items, fuel, light & water charges, domestic non-durable
goods, medicines, health fortiﬁcations, school textbooks, books, tobacco, and othermiscellaneous items.
• Total expenditure cT : The total expenditure includes, in addition to the nondurable expenditures deﬁned above, services, semidurables and durable expenditures. Housing purchases are not included.9
Again, all variables are deﬂated by the CPI.
9

For more details on the deﬁnition of expenditures, see Kitao and Yamada (2023).

7

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

2.1.4

Seasonality

Monthly earnings and expenditures exhibit seasonality, as shown in Figures 1a and 1b,which plot raw monthly earnings and total expenditures, respectively. The monthly
earnings in Japan exhibit a signiﬁcant seasonal pattern due to a unique characteristic of
the Japanese labor market, where bonuses are traditionally paid twice a year, in June(or July), and in December. Expenditures also have seasonality. For instance, education
expenditures peak in March due to tuition fee payments as the new academic (andﬁscal) year starts in April in Japan, while December marks a high season for leisure andexpenditures to prepare for the new year.

8

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

450

1100
1000
900

1981
1990
2000
2010
2020

400

1981
1990
2000
2010
2020

350

800
700

300

600

250

500
400

200
300
200
r
n
b
Ja Fe Ma

r

Ap

y

Ma

n Jul
p
g
Ju
Au Se
Month

Oc

t

150
r
n
b
Ja Fe Ma

c
v
No De

(a) Earnings yL : Raw
340

550

320

500

300

400

1981
1990
2000
2010
2020

280
260

350

240

300

220

250
r
n
b
Ja Fe Ma

r

Ap

y
Ma

n Jul
p
g
Ju
Au Se
Month

y

Ma

n Jul
p
g
Ju
Au Se
Month

t

Oc

c
v
No De

(b) Total Expenditure cT : Raw

600

450

r

Ap

1981
1990
2000
2010
2020

200
r
n
b
Ja Fe Matcv
Oc No De(c) Earnings yL : 6-months Average

r

Ap

y

Ma

n Jul
p
g
Ju
Au Se
Month

t

Oc

c
v
No De

(d) Total Expenditure cT : 6-months Average

Figure 1: Seasonality in Earnings and Total Expenditure
Source: FIES. Unit is 1,000 yen. SSY Figure 2.

To weaken the inﬂuence of seasonality, we conduct the calculations following Liseet al. (2014) and Sudo et al. (2012). For each household, we take the 6-months averageof earnings and total expenditure respectively, after controlling for monthly eﬀects byrunning a regression with monthly dummies. We drop households that did not complete
six months of survey. Since the bonuses are paid twice (summer and winter) a year
traditionally, the 6-months average of earnings will weaken the inﬂuence of seasonality
partially. In Figures 1c and 1d, we plot the 6-months average earnings yL and total
expenditure cT for each month. Note that in this calculation, one household has a one

9

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

observation for earnings and consumption even if they answer consecutive six months
for the survey. As the ﬁgures show, the seasonality patters ﬂatten for both earnings andtotal expenditure, although weak seasonality still remains.
2.1.5

Sample Selection

In this study, we follow the method of Lise et al. (2014) for sample selection for the
purpose of international comparisons and comparability with previous studies. However,as described below, in some cases we may use a diﬀerent sample to maximize the potentialof the data. We will use the following three sample selections.
Sample A: All sample The ﬁrst method is to pool all samples. In this sample, we do
not calculate the 6-months average discussed above and use all monthly data. 10 While
the sample size is large as shown in Table 1, there are some problems due to the characteristics of the FIES. In the FIES, while almost all households report their consumption
expenditures in all years, the monthly income is available only for households whose
head is employed. The data is missing for households whose head is unemployed or
self-employed.
Sample B: RED Lise et al. (2014) focus only on households whose head is an employed worker to ensure consistency among earnings, income and consumption. In addition, samples are restricted to households with heads aged between 25 and 59. There isa mandatory retirement system in Japan, and individuals typically have to retire when
they reach a certain age according to company rules. In recent years, many companies
have set the retirement age at 65 or 60; in the latter case, companies are now required
to oﬀer an opportunity to rehire the employees to continue working until age 65 after
adjusting their wages. However, our data set goes back to the 1980s. In the labor market customs in those early years, rehiring programs are not standard, and many people
retired at age 60. In fact, in the early 1980s, some companies had the retirement age
10

We use this Sample A for the analysis of consumption expenditures and our results are not aﬀectedmuch when we use monthly dummies to remove seasonality.

10

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

of 55. In addition, Japanese companies traditionally have a retirement allowance system, and many companies, especially large ones, pay large lump-sum retirement beneﬁts
upon retirement. Since retirement allowances at large companies could amount to tensof millions of yen, we focus on households with heads of household aged 59 and below
in Sample B, to eliminate the extreme inequality driven by this one-time payment.
Table 1, marked as Sample B, shows the sample size evolution when following themethod of Lise et al. (2014). First, as noted above, we compute the six-month averagefor each household to remove seasonality. There are 698,317 households that responded
for all six months. Of these, 450,381 are households whose head of household is at least
25 and less than 60. The ﬁnal sample size is 338,317 after dropping households withmissing income and consumption data and trimming the top and bottom 0.25% of thesample size.
Sample C: Quarterly Data The third dataset is quarterly data. Sample A utilizes
the entire sample, so household information in the dataset is available on a monthly
frequency. Sample B, on the other hand, averages the responses of each household over
six months so that each household has only one observation, which is then pooled by
year.11 In Sample C, we construct a quarterly data set generated from the original
monthly data. This is to create the primary data for time-series analysis since many of
the aggregate data, such as GDP, is collected quarterly.
To create the quarterly data in Sample C, we combine each household’s quarterly
income and consumption data. For households that responded from January throughJune 2000, we take January-March totals as the ﬁrst-quarter values and April-June
totals as the second-quarter values. In the case of households that began respondingin February for six months, only the second quarter values are added to the data set,
and data from other periods are not used. As in Sample B, we also limit the sample to11

For example, a household who began responding in September 1990 would have responded for six
months (September, October, November, and December in 1990, and January and February in 1991),
and it is included as a observation for 1990. On the other hand, households that started in November
are treated as a 1991 data set; if they started in October, they were treated as a 1990 data set, eventhough they responded for exactly half the time.

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ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

households whose heads are aged between 25 and 59.
Table 1: Sample Selection
Observations
Remaining
deleted observations
3,866,614
3,866,614

Original data set (1981 – 2021)
Sample A
Households who answer all the six-months
Aged less than 25 and more than 60
Non-positive/missing labor income
Non-positive/missing disposable income
Non-positive/missing consumption
Zero earnings at initial month
Trimming
Sample B
Construct quarterly series
Trimming
Sample C

3247,936
93,48717
0
14,287
4,276

698,317450,381356,897356,880
356,880
342,593338,317338,317

4,795

417,768
412,973
412,973

Inequality Over TimeIn this section, we analyze the dynamics of inequality in the Japanese economy from atime series direction.

3.1

Earnings Inequality

Figure 2 shows the trends of inequality in equivalized household earnings, based on various measures of inequality. As observed in all four ﬁgures, earnings inequality steadily
increased between 1980 and 2000 and stabilized thereafter, staying at the elevated level
for the following two decades.
As Figure 2a shows, labor income inequality, as measured by the logarithm of variance, has increased from 0.19 to 0.31 over the last 40 years. However, inequality does
not continue to increase monotonically. Labor income inequality rose throughout the
1980s. After the bubble burst around 1990, inequality remained high. It was not until

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ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

around 2000 that labor income inequality began to grow again. Since the mid-2000s,
it has again remained at a high level, as is already mentioned in Lise et al. (2014) andSudo et al. (2012).
Since the 1980s, labor income inequality in Japan has been on an upward trend, and it
is diﬃcult to ﬁnd a period when inequality has shrunk. In Figure 2a, the shaded periods
indicate recessions.12 From Figure 2a, it is diﬃcult to ﬁnd a simple relationship between
booms and busts and widening economic inequalities. However, it is a recent trendthat labor income inequality has shown a slight tendency to shrink during the boom
period after 2013, the so-called Abenomics policy period. In addition, the COVID-19
crisis that began in 2020 raised labor income inequality sharply, despite the slight labor
income inequality in the late 2010s.
There are several ways to measure economic inequality. There are cases in which
widening inequality is caused by the wealthy becoming even richer, and conversely,
there are cases in which the bottom drops further, and inequality widens. In particular,
as Piketty (2014) points out, there is a worldwide concern that wealth is becoming moreconcentrated as the rich become richer, especially in the U.S. To conﬁrm this point, let
us look at indicators other than the variance of logarithms.
Figure 2b shows the change in inequality as measured by the Gini coeﬃcient, a
representative indicator used to measure economic inequality. Compared to Figure 2a,no signiﬁcant diﬀerences are observed. Although the variance of logarithmic tends toincrease as nearly zero earners increase, there is no clear diﬀerence between the two
indicators regarding economic inequality.
Figure 2c shows the ratio of the labor income of households in the 10th percentile
to that of households in the 50th percentile for each year. In other words, as the labor
income of the bottom 10th percentile declines relative to the median, this value will
increase. The P50/P10 continued to rise moderately from 1981 to the early 2000s, after
which it stopped expanding. The rise in P90/P50 in Figure 2d created the widening gap
in the 1980s stated above. P90/P50 also re-expanded in the 2000s, but then declined
12

The recessionary period is according to the oﬃcial view of the Cabinet Oﬃce: https://www.esri.
cao.go.jp/jp/stat/di/hiduke.html.

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ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

slightly. These developments suggest that the Japanese economy has not experienced
an extreme concentration of labor income.13
0.3

0.35

0.29
0.28
0.3
0.27
0.26
0.25

0.25

0.24
0.23
0.2
0.22
0.21
0.15
1980

1985

1990

1995

2000 2005
Year

2010

2015

0.2
1980

2020

1985

1990

(a) Variance of Logarithm
2.1

2.05

2.05

2

2

1.95

1.95

1.9

1.9

1.85

1.85

1.8

1.8

1.75

1.75

1.7

1.7

1.65

1.65
1985

1990

1995

2000 2005
Year

2010

2000 2005
Year

2010

2015

2020

2010

2015

2020

(b) Gini

2.1

1.6
1980

1995

2015

1.6
1980

2020

(c) P50/P10

1985

1990

1995

2000 2005
Year(d) P90/P50

Figure 2: Various Measures of Equivalized Household Earnings Inequality
Source: FIES. Sample B is used.

To understand this trend of inequality in more details, Figure 3 shows the equivalized
household earnings and disposable income at diﬀerent percentiles. Dividing the earnings
and income values by those in 1981 for normalizaion, all percentiles indicate how muchthey have grown since 1981. As shown in Figure 3a, household earnings grew much
more rapidly in the upper percentiles from 1981 to around 2000. At the top 5, 10 and 25
13

For the evolution of concentration of income in the long-run, see, for example, Moriguchi and Saez
(2008).

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ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

percentiles, earnings in 2000 was about 40% above the level in 1981, but at the bottom
5 and 10 percentiles, earnings grew by only 20% or less during the same period. After
2000, earnings at all percentiles ceased to grow, at least until the late 2010s, which
accounts for the ﬂat path of inequality index shown in Figure 2. The paths of disposable
income are more compressed than those of earnings as shown in Figure 3b, mainly due tothe progressive labor income taxes. The disposable incomes of the bottom 5% and 10%
grew in the mid to late 2020s, while the top 5% and 10% grew relatively mildly, which
has narrowed the gap. However, the COVID-19 crisis reduced earnings and disposable
income of households who are below median levels, resulting in the widening inequality.
0.7

0.7
p5
p10
p25
p50
p75
p90
p95

0.6
0.5
0.4

0.5
0.4

0.3

0.3

0.2

0.2

0.1

0.1

0

0

-0.1
1980

1985

p5
p10
p25
p50
p75
p90
p95

0.6

1990

1995

2000 2005
Year

2010

2015

-0.1
1980

2020

(a) Equivalized Household Earnings

1985

1990

1995

2000 2005
Year

2010

2015

2020

(b) Equivalized Disposable Income

Figure 3: Percentiles of the Equivalized Household Earnings Distribution
Source: FIES. Sample B is used.

Figure 4 compares the inequality trend in earnings of household heads with thatof equivalized households. As shown in the two top panels, the level of inequality islower for equivalized earnings of households, implying that earnings of family members
mitigate inequality across households. The share of two-earner household has increased
since early 2000s, as female labor force participation has increased during this period.

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ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

0.32
0.3

0.3
Head
Household

0.29

Head
Household

0.28

0.28

0.27

0.26

0.26
0.24
0.25
0.22
0.24
0.2

0.23

0.18

0.22

0.16

0.21

0.14
1980

1985

1990

1995

2000 2005
Year

2010

2015

0.2
1980

2020

1985

1990

1995

2000 2005
Year

2010

2015

2020

(a) Head and Equivalized Household Earnings (b) Head and Equivalized Household Earnings(Var. of Log)
(Gini)
0.6

0.2
0.18

0.55

0.16
0.14

0.5

0.12
0.45

0.1
0.08

0.4

0.06
0.04

0.35

0.02
0.3
1980

1985

1990

1995

2000 2005
Year

2010

2015

0
1980

2020

(c) Proportion of Two-earner Households

1985

1990

1995

2000 2005
Year

2010

2015

2020

(d) Between-spouse Corr. of Log Earnings

Figure 4: Understanding the Role of the Family for Earnings Inequality
Source: FIES. Sample B is used.

3.2

Income Inequality

Generally, the inequality in labor income attracts much attention due to the ease ofcollecting data. However, what ultimately determines our welfare is not how much weearn in some periods, but how much we consume (and enjoy leisure). According to thepermanent income/life cycle hypothesis, the permanent income, which includes past andfuture income, determines current consumption. It is also important to consider the roleof public and private transfers in shaping income distribution. Private transfers, such16

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

as remittances from relatives, and public transfers, such as the payments based on thesocial security system, can signiﬁcantly impact an household’s income. 14 Additionally,
due to progressive income taxation, the higher the income, the higher the income tax
bracket and more taxes are deducted from income. Also, since our dataset is based onhouseholds rather than individuals, if retired adults are included as household members,
his/her public pension beneﬁt will be added to the total income. Thus, although oursample selection focuses on working households with heads aged 25-59, our results would
be aﬀected by the public pension system via cohabiting family members. There are alsosigniﬁcant diﬀerences in household composition between the 1980s and 2020s, such as theshare of individuals living with their elderly parent(s). Note that the OECD equivalentscale would adjust for some of the eﬀects of household composition but does not entirely
control for it.
Figure 5 compares the trend of inequality in earnings, pretax income, and disposable
income. Inequality does not diﬀer much between earnings and pretax income, which also
includes asset income. In the FIES, households have a relatively small amount of asset
income, and adding it does not aﬀect pre-government income inequality. However, thispoint may be due to the possibility that households under-report asset income in the
FIES. Some studies point out the same possibility with the National Survey of Family
Income and Expenditure (NSFIE), but data limitations make further analysis diﬃcult.
Inequality of disposable income is lower as the dispersion is compressed by progressive
labor income taxes. The gap between pre-government and disposable income is wider
after 2010 than in the 1980s. In other words, redistributive eﬀects of progressive income
taxes and other government policies have strengthened. In the 1980s, the progressivityof income tax in Japan was high, with the highest marginal tax rate of above 70%. As
the Reagan and Thatcher administrations lowered the marginal tax rates in the U.S.
and the U.K. in the 1980s, Japan followed suit, leading to a weaker redistributive eﬀect
of income taxation. The data apparently show the opposite relationship. How did it
happen? In the FIES, income earners who are in the highest marginal tax bracket is
14

It is worth noting that health and long-term care insurance systems are often in-kind transfers andtherefore may not be reﬂected in income from surveys like the FIES.

17

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

very few, as most of them are employed workers. Therefore, the reduction in the top
marginal tax rates does not necessarily result in higher inequality in after-tax income.
Moreover, as shown in Figure 3b, disposable income below median grew rapidly, which
contributed to a decline in inequality.
0.32
0.3

0.3
Earnings
Pretax Income
Disposable Income

0.29

Earnings
Pretax Income
Disposable Income

0.28

0.28

0.27

0.26

0.26
0.24
0.25
0.22
0.24
0.2

0.23

0.18

0.22

0.16

0.21

0.14
1980

1985

1990

1995

2000 2005
Year

2010

2015

0.2
1980

2020

(a) Earnings and Pretax Income (Var. of Log)

1985

1990

1995

2000 2005
Year

2010

2015

2020

(b) Earnings and Pretax Income (Gini)

Figure 5: From Earnings to Disposable Income
Source: FIES. Sample B is used.

3.3

Consumption Inequality

Figure 6 shows that consumption and disposable income tend to move in the same direction, as also indicated by the positive covariance in Figure 6a. Although inequality
in disposable income declined since the mid-2010s, inequality in consumption remains
ﬂat, resulting in a mild decline in covariance. Consumption of non-durable goods exhibits lower inequality than total consumption. Non-durable goods consists of items
that are typically essential for all households, such as general food items and utility
charges and tend to vary less across households compared to durable goods and services.
This pattern is consistent with the standard consumption smoothing theory. That is,households adjust their consumption across time so that the marginal utilities are equalintertemporally. Consumption smoothing is easier for non-durable goods and more diﬃ-

18

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

cult for durable goods, purchased less frequently and more expensive. 15 This contributes
to higher inequality of total and durable consumption expenditures than that of nondurable expenditures.16
It is an interesting observational fact that the most recent decade has seen a divergence in disposable income and consumption inequality trends. Until around 2008,
when Lise et al. (2014) and Sudo et al. (2012) conducted their analysis, income andconsumption inequality had been moving almost parallel. Why have they diverged inrecent years?
One possibility is that the nature of the idiosyncratic risk faced by households may
have changed. As noted by Storesletten et al. (2004) and Blundell et al. (2008), households’ labor income faces idiosyncratic risks of a diﬀerent nature; persistent and temporary shocks. Temporary shocks are iid shocks determined each period; for example, theJapanese bonus system is uncorrelated with the previous period. 17 On the other hand,a persistent shock is one that, once realized, aﬀects earnings over a long period, suchas a wage base increase or promotion. In both cases, as the shock size increases, theinequality measured by the variation in a particular year appears to widen. However, as
Blundell et al. (2008), Okubo (2015) and Kubota (2020) have analyzed, consumption responds to changes in permanent income but rarely to temporary income shocks. Thus, if
the size of persistent shocks increases while temporary shocks decrease, income inequality may remain constant or decrease slightly, but consumption inequality may increase.
Another possibility is the presence of unrealized capital gains of stocks or upsurge ofhousehold assets. Japanese stock prices rose substantially during the Abenomics policy
period. However, the income inequality in the data has not increased without sellingstocks/assets. Under these circumstances, households holding stocks make consumption
decisions based on their unrealized but inﬂated lifetime assets, thus creating a discrep-

15

Higa (2019) discusses the possibility of under-reporting of durable goods purchase due to survey
fatigue.
16
For mode details on the consumption smoothing and consumption insurance, see Kaplan and Violante (2010), Attanasio and Pistaferri (2014, 2016) and Aguiar and Bils (2015).
17
More precisely, bonuses may not be iid shocks since the bonus payments depend on ﬁrm performancewith the business cycle, which is persistent for several years.

19

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

ancy between income inequality and consumption inequality movements. Various otherhypotheses are possible, but this point requires further research based on theoreticalmodels.18
0.3

0.28
0.26
0.24

Disposable Income
Non-durable Consumption
Total Consumption
Covariance

0.28

Disposable Income
Non-durable Consumption
Total Consumption

0.26

0.22
0.2

0.24

0.18
0.22

0.16
0.14

0.2

0.12
0.18

0.1
0.08
1980

1985

1990

1995

2000 2005
Year

2010

2015

0.16
1980

2020

1985

1990

1995

2000 2005
Year

2010

2015

2020

(a) Equiv. Disposable Income and Consump- (b) Equiv. Disposable Income and Consumption (Var. of Log)tion (Gini)
2

1.9

2
Disposable Income
Non-durable Consumption
Total Consumption

1.9

1.8

1.8

1.7

1.7

1.6

1.6

1.5

1.5

1.4
1980

1985

1990

1995

2000 2005
Year

2010

2015

1.4
1980

2020

Disposable Income
Non-durable Consumption
Total Consumption

1985

1990

1995

2000 2005
Year

2010

2015

2020

(c) Equiv. Disposable Income and Consumption (d) Equiv. Disposable Income and Consump(P50/P10)
tion (P90/P50)

Figure 6: From Disposable Income to Consumption
Source: FIES. Sample B is used.

Figure 7 shows the changes in equivalized consumption expenditures at diﬀerent
percentiles. As shown in Figure 7a, the level of non-durable expenditures at the top
5 and 10 percentiles grew rapidly, reaching 20% above the level of 1980 by the late18

Based on the U.S. data, Krueger and Perri (2006) explain that income inequality and consumption
inequality are not necessarily linked in the limited enforcement model.

20

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

1990s, and stayed at the same level until around 2010. Non-durable expenditures at thebottom 5 and 10 percentiles grew more slowly initially and started to decline after thelate 1990s, falling below the level of 1980 by the late 2000s. The path of equivalized total
consumption expenditures show a similar trend until around 2000, but the consumption
level remained stable for all percentiles thereafter, accounting for a diﬀerent time pathof inequality index in Figure 6 above.
0.4

0.4
p5
p10
p25
p50
p75
p90
p95

0.35
0.3
0.25

0.3
0.25

0.2

0.2

0.15

0.15

0.1

0.1

0.05

0.05

0

0

-0.05

-0.05

-0.1
1980

1985

p5
p10
p25
p50
p75
p90
p95

0.35

1990

1995

2000 2005
Year

2010

2015

-0.1
1980

2020

(a) Equivalized Non-durable Expenditure

1985

1990

1995

2000 2005
Year

2010

2015

2020

(b) Equivalized Total Expenditure

Figure 7: Percentiles of the Equivalized Household Expenditure Distribution
Source: FIES. Sample B is used.

4

Inequality Over the Life Cycle

4.1

Demographic Changes in JapanThe Japanese economy has experienced many changes over the past four decades. Oneof the most signiﬁcant changes that has impacted the long-term transition is the shift in
the demographic structure. With a rise in life expectancy, the birth rate has declined,leading to a decrease in the number of children and then the working generation. In
Figure 8, we show the age distribution in our FIES sample in 1981 and 2021, as wellas the distribution from the Census Survey. The peak of the age distribution in 1981
was at the baby boom generations aged around 35 then, who were born in the late
1940s. In 2021, there are two peaks, the ﬁrst baby boom generations now in their 70s,

21

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

and their children aged around 50. As shown in Figure 8d, the population falls almost
monotonically below age 50 due to low fertility rates below the replacement rate since

4

4

3

3

Percent

Percent

the early 1970s. The same pattern is observed among our FIES samples.

2

1

2

1

0

20

40

60

80

0

100

20

40

Age of Household Head

80

100

(b) Year 2021: FIES

2500

2500

2000

2000

1500

1500

Unit: 1,000

Unit: 1,000(a) Year 1981: FIES

1000

500

0

60

Age of Household Head

1000

500

0

20

40

60

80

0

100

0

20

Age

40

60

80

100

Age

(c) Year 1981: Census Survey(d) Year 2020: Census Survey

Figure 8: Changing Age Distribution
Source: FIES and Population Census Survey.

4.2

Inequality by Age Controlling for Time and Cohort Eﬀects

We now demonstrate how the inequalities of earnings, income and consumption evolve
over the life cycle. The estimation procedure is as follows. First, we calculate thevariance of the logarithm of each variable for each age by calendar year or cohort. 19 For
example, Xt,j is the variance of the logarithm of labor income for age j in year t (or19Regarding issues associated with the control of year and cohort eﬀects, see Heathcote et al. (2005).

22

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

cohort t).20 We then regress Xt,j on age and calendar year/cohort, and plot the age
eﬀects.
Figure 9 shows age proﬁles of various indicators inequality among our FIES samples.
In the estimation, we control for time and cohort eﬀects and extract the component thatvaries by age only. Inequality of earnings and disposable income monotonically increases
between 25 and 59, and the latter grows more mildly because of the redistributive policies
such as progressive income taxation and transfers.
The rising inequality in labor income and disposable income by age is similar to theﬁndings in previous studies.21 Labor income inequality is relatively small at young ages,
either because human capital accumulation is insuﬃcient to exhibit large dispersion, or
because employers do not know the extent of the individual employees’ ability. However,as human capital accumulates with age, diﬀerences in wages also emerge. 22 In addition,
because of the accumulation of permanent income shocks, the variance of the logarithmsof labor income tends to increase with age, and this is commonly observed in many
countries.
As explained in Section 3.3, rising income inequality does not necessarily imply awidening of consumption inequality. Households can smooth consumption by mitigating various shocks through precautionary savings and by various kinds of insurances.
However, while temporary shocks could be intertemporally smoothed with the withdrawal and accumulation of the precautionary savings, persistent income shocks are
more diﬃcult to alleviate, and thus, consumption inequality rises with age. Figure 9shows that the age proﬁle of non-durable consumption is very ﬂat, and diﬀerences by
age are not so pronounced. On the other hand, the age proﬁle of total consumption ischaracterized by a convex shape. As also noted by Abe and Yamada (2009), the total
consumption inequality proﬁle tends to be ﬂat or declines gradually with age from the20

In the estimation, we create the cohort dummies for 5-year increments, starting from the generation
born in 1925-1929. The original mean and the variance of log proﬁles by cohort are summarized inAppendix A.
21See, for example, Heathcote et al. (2010) and Krueger et al. (2010)22
For earlier papers on the issues of human capital accumulation over the life cycle and the estimatesof wage dynamics, see, for example, Heckman et al. (1998) and Guvenen (2007).

23

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

20s to around 40, and then begins to rise. No clear explanation has yet been provided
as to why this trend occurs, but it is similarly observed in life cycle proﬁles using themost recent data.
0.3
0.25

0.3
Household Earnings
Disposable Income
Non-durable Consumption
Total Consumption

0.25

0.2

0.2

0.15

0.15

0.1

0.1

0.05

0.05

0

0

-0.05

-0.05

-0.1
25

30

35

40

45

50

55

-0.1
25

60

Household Earnings
Disposable Income
Non-durable Consumption
Total Consumption

30

35

40

Year

45

50

55

60

Year

(a) Var. of log Raw (Control for Year Eﬀects) (b) Var. of log Raw (Control for Cohort Eﬀects)
0.3
0.25

0.3
Household Earnings
Disposable Income
Non-durable Consumption
Total Consumption

0.25

0.2

0.2

0.15

0.15

0.1

0.1

0.05

0.05

0

0

-0.05

-0.05

-0.1
25

30

35

40

45

50

55

-0.1
25

60

Year

Household Earnings
Disposable Income
Non-durable Consumption
Total Consumption

30

35

40

45

50

55

60

Year

(c) Var. of log Equivalized (Control for Year (d) Var. of log Equivalized (Control for Cohort
Eﬀects)Eﬀects)f
Figure 9: Life Cycle Inequality: Controlling for Time and Cohort Eﬀects
Source: FIES. Sample B is used.

4.3

More on Life Cycle Consumption

Although consumption is relatively smooth over the life cycle compared to earnings andincome, and inequality is lower, consumption expenditures are far from constant overthe life cycle. In this section, we examine characteristics of consumption expenditures

24

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

over the life cycle in more detail. The FIES classiﬁes expenditures recorded in household
accounts into four categories: (i) non-durable, (ii) service, (iii) semi-durable, and (iv)
durable expenditures. Semi-durable expenditures are combined with durable expenditures to focus on the three categories of non-durable, durable, and service expenditures.
Figure 10 shows the life cycle proﬁles of total consumption and the three categories,
with only the age eﬀects extracted from the estimation.23
Total consumption exhibits a hump-shape, as shown in Figure 10a. The age proﬁles,
however, signiﬁcantly diﬀer by consumption categories and by items, as shown in Figures 10b to Figures 10d. It is well known in the literature that the total consumption
proﬁle is hump-shaped, resembling the inverse U-shaped labor income proﬁle associated with human capital accumulation, the seniority wage system, and other factors. 24
However, the decomposition of expenditures reveals diﬀerent patterns over the life cycle.
Non-durable consumption expenditures increase until around age 40, but after that, theyremain almost ﬂat, with little change by age. Consumption smoothing as implied by the
Euler equation is a basic foundation in macroeconomics. From Figure 10b, households
are observed to smooth their non-durable expenditures intertemporally except for their
younger ages when they may face liquidity constraints. Conversely, durable expenditures
exhibit a hump-shape, similar to total consumption. Since individuals consume durable
goods over a long period after purchase, they tend to purchased more often when they
are young and middle-aged, and they are less likely to make as many new purchases
after retirement. Service spending declines almost monotonically with age. The decomposition analysis reveals that the hump-shaped total consumption proﬁle results from a
mix of expenditures of these diﬀerent categories.

23
Our sample consists of households headed by individuals aged between 25 and 80, using data fromthe years 1987 to 2020. The following model is estimated.
age
cohortln Cit = β0 + βage Dit+ βc Dit+ βt Dyear + βm Dmonth + βfam Xit + ϵit

(1)

age
k
where Cit
is expenditure of household i in period t on consumption item k, Dit
is a vector of age
dummies. All items are deﬂated using the CPI of each items. For more details on the data andestimation procedure, see Kitao and Yamada (2023).
24
For more on the life cycle consumption proﬁle, see, for example, Gourinchas and Parker (2002) andFerńandez-Villaverde and Krueger (2007).

25

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

180

90

175
85
Expenditures in 1,000 yen

170
165
160
155
150
145
140

80
75
70
65
60
55

135
130
30

40

50
Year

60

70

50

80

30

(a) Total Consumption

60

70

80

70

80

70
65
Expenditures in 1,000 yen

18
Expenditures in 1,000 yen

50
Year

(b) Non-durable

20

16

14

12

10

8

40

60
55
50
45
40
35

30

40

50
Year

60

70

30

80

(c) Durable

30

40

50
Year

60

(d) Services

Figure 10: Life Cycle Proﬁles by Category
Source: FIES. Unit: 1,000 yen. Sample A is used.

Further disaggregation of expenditures reveals even more diverse expenditure patterns over the life cycle. Figure 11 shows expenditures of nine ﬁner categories: (a) food,(b) housing, (c) fuel, light and water, (d) furniture, (e) clothes and footwear, (f) medicalcare, (g) transportation and communication, (h) education, and (i) culture and recreation. Adding other expenditure items (including unknown expenditures such as sending
money home to parents) to the sum of these nine categories yields total consumption.
Figure 12 plots the coeﬃcients of age dummies. At the ﬁrst glance, expenditure
proﬁles of some items are hump-shaped, some are monotonically increasing, and others
are decreasing. On the one hand, items such as clothing and shoes, for which people

26

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

tend to spend much more when they are young and less when they are old, show adecreasing proﬁle. On the other hand, medical care spending rises sharply after theirlate 50s. Education spending starts to rise in their late 30s and reaches its maximum attheir mid-50s, as spending increases when their children, rather than themselves, startattending high school and continue to college. Transportation spending increases withage but peaks and declines in their late 50s. This item includes a mix of transportationand communication expenses. As Aguiar and Hurst (2013) point out, transportation
expenses are high during the working period but decline once individuals retire, because
they are less likely to go far away from home as often. Note that “housing” here refers
to house maintenance and other expenses, not house purchases, which are not includedin the expenditure data.

27

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

52

19

48
46
44
42

Expenditures in 1,000 yen

30
Expenditures in 1,000 yen

Expenditures in 1,000 yen

50

25

20

15

10

40
38

20

35

30

40

50
Year

60

70

5

80

16
15

30

40

50
Year

60

70

13

80

(b) Housing

5.5

2.2

9

5

1.8
1.6
1.4
1.2
1

8
7
6
5
4

30

40

50
Year

60

70

2

80

30

40

50
Year

60

70

60

70

80

4
3.5
3

2

80

30

40

50
Year

60

70

80

70

80

(f) Medical Care
8

12

7.5

12

10
9
8

Expenditures in 1,000 yen

Expenditures in 1,000 yen

11

11

10

9

8

7
6.5
6
5.5
5
4.5

7

7
6

50
Year

4.5

(e) Clothes and Footwear(d) Furniture
13

40

2.5

3

0.8
0.6

Expenditures in 1,000 yen

10

2

30

(c) Fuel, Light and Water

2.4

Expenditures in 1,000 yen

Expenditures in 1,000 yen

1714(a) Food

Expenditures in 1,000 yen

18

4
30

40

50
Year

60

70

80

(g) Transp. and Communication

6

30

40

50
Year

60

(h) Education

70

80

3.5

30

40

50
Year

(i) Culture and Recreation

Figure 11: life cycle Proﬁles of Consumption by Item Groups
Source: FIES. Sample A is used.

28

60

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

0.4

1
0.9

0.2

0.8

-0.4

Age Effects

Age Effects

Age Effects

-0.2

-0.8

0.5

0.7

0

-0.6

1
Fuel
Medical Care
Trans. Com
Education

0.6
0.5
0.4

0

-0.5

0.3
Total
Non-durable
DurableService

30

40

0.2

-1

0.1
50
Year

60

70

80

0

(a) By Categories

30

40

50
Year

60

(b) Group (1)

70

80

-1.5

Food
Clothes
Housing
Cultiure and Rec.

30

40

50
Year

60

70

80

(c) Group (2)Figure 12: Age Eﬀects of Consumption by Categories
Source: FIES. Sample A is used.

4.4

Variance of Residuals

Figures 13 and 14 plot the proﬁle of expenditure inequality by age, where we use Sample
A. Following Aguiar and Hurst (2013), each consumption variable is regressed on household characteristics such as family structure, and time and cohort dummies, and thenwe calculate the variance of the logarithm of residuals by age. Figure 13 reveals that theconsumption inequality follows a convex path from age 25 to 60, decreasing initially from25 to 35 and rising sharply thereafter. However, as with the mean levels of consumption
expenditures, the shapes of the variance of the logarithm proﬁle vary by the expenditure
items, as shown in 14. For example, the variance in food expenditures is the smallest
at around age 40, but it is nearly ﬂat, staing in a narrow range between 0.15 and 0.20
over the life cycle. Non-durable expenditures follow a convex proﬁle, reaching the lowest
level at around age 40, while the variation in service and durable goods expenditures
increases with age.

29

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

Variance of Logarithm

0.35

0.3

0.25

0.2

30

40

50
Year

60

70

80

Figure 13: Variance of Residuals of Total Consumption
Source: FIES. Sample A is used.

30

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

Non-durable
Service (right axis)
Durable (right axis)

1.6

0.4

1.4
0.16
1.2
0.15
1
0.14
0.8

0.35
0.3
0.25
0.2
0.15
0.1

0.13

0.12

Food
Fuel

0.45

Variance of Logarithm

0.17

Variance of Logarithm

0.5

1.8

0.18

0.6

30

40

50
Year

60

70

0.05
0

0.4
80

30

(a) By Categories

50
Year

60

70

80

70

80

(b) Group (1)
4.5

1.8
1.7

40

Trans Com
Medical Care
Culture4

ClothesHome
Education

Variance of Logarithm

Variance of Logarithm

1.6
1.5
1.4
1.3
1.2
1.1

3.5
3
2.5
2

1
1.5

0.9
0.8

30

40

50
Year

60

70

1

80

(c) Group (2)

30

40

50
Year

60

(d) Group (3)Figure 14: Variance of Residuals of Consumption by Categories and Item Groups
Source: FIES. Sample A is used.

5

Conclusion

This paper has analyzed economic inequality in Japan from 1981 to 2021 using theFamily Income and Expenditure Survey. During this period, earnings, income, andconsumption inequality increased. However, the pattern of this increase was neither
monotonic nor uniform across the three variables; there were some periods of risinginequality and other periods of stabilization. Labor income inequality increased in the
1980s and early 2000s. While it has remained high in the recent decade, it has not
risen further from that level. Conversely, inequality in disposable income, calculated by

31

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

adding capital income and public transfers to labor income and subtracting taxes, hasdeclined in the 2010s, corresponding to the Abenomics policy period. From our analysis,
it remains to be determined whether this trend is due to some speciﬁc policy or otherreasons, requiring further investigation.
Compared to the trend of earnings and income inequality trends, the dynamics ofconsumption inequality is diﬀerent. In the past, consumption inequality moved almostin parallel with disposable income inequality. However, since the mid-2010s, disposable
income inequality has been gradually declining, while consumption inequality has been
rising, albeit slightly. Further research with a theoretical model is needed to investigate
this issue.
Demographic changes continue to have a signiﬁcant long-term impact on the Japanese
economy. As is well known, earnings and income inequality tends to increase with age.
While this ﬁnding is not new, we conﬁrm that the relationship still holds when we add
data over the last decades.
Consumption inequality proﬁles over the life cycle show complex movements. The
variance of the logarithm of the total consumption follows a convex path over the life
cycle, with a gradual decline in consumption inequality from young to middle ages,
followed by an increase. Moreover, the variation of individual items shows diﬀerent
patters.
In summary, the fact that disposable income inequality has decreased during themost recent economic expansion would be an interesting ﬁnding. However, income inequality has started to rise again during the COVID-19 crisis. What happened since thepandemic remains to be conﬁrmed with additional data, and we must carefully analyze
future trends. Our study provides fundamental materials for examining the relationshipbetween economic inequality and the macroeconomy. Our results also oﬀer calibration
targets that should be reconciled in the construction of structural macro models andin conducting various policy analyses pertaining to economic inequality. The exploration of various policy analyses related to economic inequality, using dynamic generalequilibrium models, is a subject of future research.

32

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

A

Life Cycle Proﬁles by Cohorts

Figure A.1 shows the mean and variance of the logarithms of age proﬁle for total consumption and annual income for diﬀerent cohorts.
16

400

15
14
Unit: 1,000

Unit: 1,000

350

1940-1944
1950-1954
1960-1964
1970-1974
1980-1984

300

250

1940-1944
1950-1954
1960-1964
1970-1974
1980-1984

13
12
11
10

200

9
150

30

40

50
Age

60

70

8

80

(a) Mean: Equivalized Annual Income

0.3
Variance of Logarithm

Variance of Logarithm

50
Age

60

70

80

0.35
1940-1944
1950-1954
1960-1964
1970-1974
1980-1984

0.25

0.2

0.15

0.1

40

(b) Mean: Equivalizd Total Consumption

0.35

0.3

30

1940-1944
1950-1954
1960-1964
1970-1974
1980-1984

0.25

0.2

0.15

30

40

50
Age

60

70

0.1

80

(c) Varlog: Equivalized Annual Income

30

40

50
Age

60

70

80

(d) Varlog: Equivalized Total Consumption

Figure A.1: Mean and Variance of Logarithm by Cohort
Source: FIES. Sample A is used.

B

Inequalities Over Business Cycle

Figures B.1 – B.3 in this section show the paths of inequality indexes based on quarterly
data of earnings, pre-government income, disposable income, non-durable expenditure,33

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

and total consumption. Because the original series of inequality is very volatile as shownin Figure B.4, we compute the moving average of each series of data.25
0.35

0.32

0.3

0.3

0.28
0.25
0.26
0.2
0.24
Earnigs
Pretax Income
Disposable Income
Non-durable Consumption
Total Consumption

0.15

0.1

1985

1990

1995

2000 2005
Year

2010

2015

Earnigs
Pretax Income
Disposable Income
Non-durable Consumption
Total Consumption

0.22

0.2

2020

1985

1990

(a) Variance of Logarithm
2.2

2.1

2.1

2

2

1.9

1.9

1.8

1.8

1.5

1.7

Earnigs
Pretax Income
Disposable Income
Non-durable Consumption
Total Consumption

1.6

1985

1990

1995

2000 2005
Year

2010

2015

2000 2005
Year

2010

2015

2020

(b) Gini

2.2

1.7

1995

Earnigs
Pretax Income
Disposable Income
Non-durable Consumption
Total Consumption

1.6
1.5

2020

(c) P50/P10

1985

1990

1995

2000 2005
Year

2010

2015

2020

(d) P90/P50

Figure B.1: Quarterly Series of Inequality in Earnings, Income and Consumption
Source: FIES. Sample C is used.

25

For recent progress on the understanding of the relationship between economic inequality andbusiness cycle, see Heathcote et al. (2020) and Bilbiie et al. (2023).

34

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

1600
1400
1200

1600
Q1
Q2
Q3
Q4
Q5

1400
1200

1000

1000

800

800

600

600

400

400

200

200

0

0
1985

1990

1995

2000 2005
Year

2010

2015

2020

1985

(a) Earnings yL

1990

1995

2000 2005
Year

2010

2015

2020

(b) Pre-government Income: y
600

1200

1000

Q1
Q2
Q3
Q4
Q5

Q1
Q2
Q3
Q4
Q5

500

800

400

600

300

400

200

200

100

Q1
Q2
Q3
Q4
Q5

0

0
1985

1990

1995

2000 2005
Year

2010

2015

1985

2020

(c) Disposable Income: yD

1990

1995

2000 2005
Year

2010

2015

2020

(d) Non-durable Expenditure: cN D

600

500

Q1
Q2
Q3
Q4
Q5

400

300

200

100

0
1985

1990

1995

2000 2005
Year

2010

2015

2020

(e) Total Consumption: cT

Figure B.2: Quarterly Series of Each Quintiles of Earnings, Income and Consumption
Source: FIES. Unit: 1,000 yen. Sample C is used.

35

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

0.6

0.6
p5
p10
p25
p50
p75
p90
p95

0.5
0.4

p5
p10
p25
p50
p75
p90
p95

0.5
0.4

0.3

0.3

0.2

0.2

0.1

0.1

0

0

-0.1

-0.1
1985

1990

1995

2000 2005
Year

2010

2015

2020

1985

(a) Earnings: yL

1990

1995

2000 2005
Year

2010

2015

2020

(b) Pre-government Income: y

0.6

0.4
p5
p10
p25
p50
p75
p90
p95

0.5
0.4

0.35
0.3
0.25

p5
p10
p25
p50
p75
p90
p95

0.2

0.3

0.15

0.2
0.1
0.05

0.1

0

0
-0.05

-0.1

-0.1

1985

1990

1995

2000 2005
Year

2010

2015

2020

1985

(c) Disposable Income: yD

1990

1995

2000 2005
Year

2010

2015

2020

(d) Non-durable Expenditure: cND

0.4
0.35
0.3
0.25

p5
p10
p25
p50
p75
p90
p95

0.2
0.15
0.1
0.05
0
-0.05
-0.1
1985

1990

1995

2000 2005
Year

2010

2015

2020

(e) Total Consumption: cT

Figure B.3: Quarterly Series of Percentiles of Earnings, Income and Consumption
Source: FIES. Sample C is used.

36

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

Variance of Logarithm

0.45
0.4
0.35

0.32
0.3

0.3

0.28

0.25

0.26

0.2

0.24

0.15

0.22

0.1

1985

1990

1995

2000 2005
Year

Gini

0.34

Earnigs
Pretax Income
Disposable Income
Non-durable Consumption
Total Consumption

2010

2015

0.2

2020

Earnigs
Pretax Income
Disposable Income
Non-durable Consumption
Total Consumption

1985

1990

(a) Variance of Logarithm

2.4
2.3
2.2

2.4
2.3
2.2
2.1

2

2

1.9

1.9

1.8

1.8

1.7

1.7

1.6

1.6
1985

1990

1995

2000 2005
Year

2010

2015

2010

2015

2020

2010

2015

2020

P90/P50

2.5

Earnigs
Pretax Income
Disposable Income
Non-durable Consumption
Total Consumption

2.1

1.5

2000 2005
Year(b) Gini

P50/P10

2.5

1995

1.5

2020

(c) P50/P10

Earnigs
Pretax Income
Disposable Income
Non-durable Consumption
Total Consumption

1985

1990

1995

2000 2005
Year(d) P90/P50

Figure B.4: Quarterly Series of Unadjusted Inequality Measures
Source: FIES. Sample C is used.

37

ESRI Disucussion Paper Series No.392"Inequality Dynamics in Japan, 1981-2021"

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